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Articles 1 - 8 of 8
Full-Text Articles in Non-linear Dynamics
Quantum Mechanics As A Framework For Data Assimilation And Its Application To Atmospheric Parameterization, David Freeman
Quantum Mechanics As A Framework For Data Assimilation And Its Application To Atmospheric Parameterization, David Freeman
Dartmouth College Ph.D Dissertations
Quantum mechanics, as a mathematical system, can be understood as a generalization of classical probability theory. Quantum Mechanical Data Assimilation (QMDA) is a method in which classical dynamical systems are embedded into a quantum mechanical setting, with an associated data assimilation scheme leveraging the operator algebraic setting. In this dissertation, the algebraic structure underlying the operator theoretic formulation of QMDA is discussed. A procedure for closure of dynamical systems based on QMDA, known as Quantum Mechanical Closure (QMCl), is then constructed, and the procedures for constructing the quantum embeddings and implementing QMCl in practice are laid out and implemented for …
Grokking Applied To Chaotic Iterates Of The Logistic Map, Felix Donkoh
Grokking Applied To Chaotic Iterates Of The Logistic Map, Felix Donkoh
Electronic Theses and Dissertations
This thesis investigates grokking, the delayed transition from memorization to generalization in neural networks trained on deterministic chaotic data. Using an integer–arithmetic discretization of the logistic map, yn+1 =( a yn(p − yn))/ p 2 , bounded aperiodic sequences were generated across control parameters α ranging from 3.0 to 4.0. Transformer-based models displayed characteristic grokking curves. In periodic and chaotic regimes, validation accuracy rose suddenly after long plateaus, while at the Feigenbaum boundary (α ≈ 3.57) generalization failed completely. Increasing data diversity restored learning in chaotic domains, and explicit α–conditioning enabled a single network to generalize across all regimes. A …
Parallel Multigrid In Time For Chaotic Dynamical Systems, David Alan Vargas
Parallel Multigrid In Time For Chaotic Dynamical Systems, David Alan Vargas
Mathematics & Statistics ETDs
Despite the fact that Parallel-in-Time (PinT) methods are predicted to become necessary to fully utilize next-generation exa- and zettascale machines, there are currently no known practical methods which scale well with the length of the time-domain for chaotic problems, due to exponential dependence of the condition number on the fastest chaotic timescale. I present modifications to the coarse-grid equations along with a novel rediscretization approach which together greatly improve convergence of the multigrid reduction in time (MGRIT) algorithm and allow the first known PinT speedup for a chaotic PDE. The novel Local Shadowing Relaxation (LSR) is presented as an alternative …
Exploring The Presence Of Nonlinear Deterministic Dynamics In Commodity Prices, Sagar Dahal
Exploring The Presence Of Nonlinear Deterministic Dynamics In Commodity Prices, Sagar Dahal
Department of Agricultural Economics: Dissertations, Theses, and Student Research
Determining whether commodity prices (and volatility) are driven by linear stochastic processes or low-dimensional nonlinear deterministic dynamics (“chaos”) is crucial for policymaking, forecasting, production, storage, investment, risk management, and hedging decisions. Previous studies that used Lyapunov exponents and correlation dimensions to identify chaotic structures in price series may be unreliable in practical applications because these methods rely on asymptotic properties that require large, noiseless data which is often not available. We applied nonlinear time series analysis approaches to empirically detect the underlying market dynamics using the daily futures prices of ten agricultural commodities. We used phase space reconstruction to reconstruct …
A Novel Method For Sensitivity Analysis Of Time-Averaged Chaotic System Solutions, Christian A. Spencer-Coker
A Novel Method For Sensitivity Analysis Of Time-Averaged Chaotic System Solutions, Christian A. Spencer-Coker
Theses and Dissertations
The direct and adjoint methods are to linearize the time-averaged solution of bounded dynamical systems about one or more design parameters. Hence, such methods are one way to obtain the gradient necessary in locally optimizing a dynamical system’s time-averaged behavior over those design parameters. However, when analyzing nonlinear systems whose solutions exhibit chaos, standard direct and adjoint sensitivity methods yield meaningless results due to time-local instability of the system. The present work proposes a new method of solving the direct and adjoint linear systems in time, then tests that method’s ability to solve instances of the Lorenz system that exhibit …
Dynamic Parameter Estimation From Partial Observations Of The Lorenz System, Eunice Ng
Dynamic Parameter Estimation From Partial Observations Of The Lorenz System, Eunice Ng
Theses and Dissertations
Recent numerical work of Carlson-Hudson-Larios leverages a nudging-based algorithm for data assimilation to asymptotically recover viscosity in the 2D Navier-Stokes equations as partial observations on the velocity are received continuously-in-time. This "on-the-fly" algorithm is studied both analytically and numerically for the Lorenz equations in this thesis.
The Effects Of Finite Precision On The Simulation Of The Double Pendulum, Rebecca Wild
The Effects Of Finite Precision On The Simulation Of The Double Pendulum, Rebecca Wild
Senior Honors Projects, 2010-2019
We use mathematics to study physical problems because abstracting the information allows us to better analyze what could happen given any range and combination of parameters. The problem is that for complicated systems mathematical analysis becomes extremely cumbersome. The only effective and reasonable way to study the behavior of such systems is to simulate the event on a computer. However, the fact that the set of floating-point numbers is finite and the fact that they are unevenly distributed over the real number line raises a number of concerns when trying to simulate systems with chaotic behavior. In this research we …
Practical Chaos: Using Dynamical Systems To Encrypt Audio And Visual Data, Julia Ruiter
Practical Chaos: Using Dynamical Systems To Encrypt Audio And Visual Data, Julia Ruiter
Scripps Senior Theses
Although dynamical systems have a multitude of classical uses in physics and applied mathematics, new research in theoretical computer science shows that dynamical systems can also be used as a highly secure method of encrypting data. Properties of Lorenz and similar systems of equations yield chaotic outputs that are good at masking the underlying data both physically and mathematically. This paper aims to show how Lorenz systems may be used to encrypt text and image data, as well as provide a framework for how physical mechanisms may be built using these properties to transmit encrypted wave signals.